Modular multiplication and division algorithms based on continued fraction expansion
|
|
- Stephany Griffith
- 5 years ago
- Views:
Transcription
1 205 IEEE 22nd Symposum on Computer Arthmetc Modular multplcaton and dvson algorthms based on contnued fracton expanson Mourad Goucem UPMC Unv Pars 06 and CNRS UMR 7606, LIP6, 4 place Jusseu, F-75252, Pars cedex 05, France Contact: goucem.mourad@gmal.com Abstract In ths paper, we provde new methods to generate a class of algorthms computng modular multplcaton and dvson. All these algorthms rely on sequences derved from the Eucldean algorthm for a well chosen nput. We then use these sequences as number scales of the Ostrowsk number system to construct the result of ether the modular multplcaton or dvson. I. INTRODUCTION Contnued fractons are commonly used to provde best ratonal approxmatons of an rratonal number. Ths sequence of best ratonal approxmatons (p /q ) N s called the convergents sequence. In the begnnng of the 20 th century, Ostrowsk ntroduced number systems derved from the contnued fracton expanson of any rratonal α []. He proved that the sequence (q ) N of the denomnators of the convergents of any rratonal α forms a number scale, and any nteger can be unquely wrtten n ths bass. In the same way, the sequence (q α p ) N also forms a number scale. In ths paper, we show how such number systems based on contnued fracton expansons can be used to perform modular arthmetc, and more partcularly modular multplcaton and modular dvson. The presented algorthms are of quadratc complexty lke many of the exstng mplemented algorthms [2, Chap. 2.4]. Furthermore, they present the advantage of beng only based on the extended Eucldean algorthm, and to ntegrate the reducton step. In the followng, we wll frst ntroduce notatons and some propertes of the number systems based on contnued fracton expansons n Secton II. Then we descrbe the new algorthms n Secton III. Fnally, we gve elements of complexty analyss of these algorthms n Secton IV, and perspectves n Secton VI. II. NUMBER SYSTEMS AND CONTINUED FRACTIONS A. Notatons Frst, we gve some notatons on the contnued fracton expanson of an rratonal α wth 0 <α< [3]. We call the tals of the contnued fracton expanson of α the real sequence (r ) N defned by r 0 = α, r =/r /r. We denote (k ) N the nteger sequence of the partal quotents of the contnued fracton expanson of α. They are computed as k = /r.wehave α = := [0; k,k 2,...,k + r ]. k + k k + r We wrte p /q the th convergent of α. The sequences (p ) N and (q ) N are nteger valued and postve, p =[0;k,k 2,...,k ]. q We wll also wrte (θ ) N the postve real sequence of ( ) (q α p ) whch we call the sequence of the partal remanders as they are related to the tals by r = θ /θ. Hereafter, we recall the recurrence relatons to compute these sequences, p = p 0 =0 p = p 2 + k p, q =0 q 0 = q = q 2 + k q, θ = θ 0 = α θ = θ 2 k θ. We also wrte η = q α p the sequence of the sgned partal remanders, whch elements are of sgn ( ). The sequence (η ) N of the sgned partal remanders can be computed as (( ) θ ) N /5 $ IEEE DOI 0.09/ARITH
2 B. Related number systems over rratonal numbers In ths secton, we present two number systems based on the sequences of the sgned partal remanders (η ) N and the denomnators of the convergents (q ) N of an rratonal α. They have been extensvely studed durng the second part of the 20 th century [], [4]. Property II. ([, Proposton ]). Gven (q ) N the denomnators of the convergents of any rratonal 0 < α<, every postve nteger N can be unquely wrtten as m N =+ n q where the followng Markovan condtons are verfed: { 0 n k, 0 n k, for 2, n =0f n + = k + Ths number system assocated to the (q ) N s named the Ostrowsk number system. To wrte an nteger n ths number system, we use a classcal greedy decomposton algorthm (Algorthm ). The rank m s chosen such that q m >N. Algorthm : Integer decomposton n Ostrowsk number system. nput : N N, (q ) <m m output: n such that N =+ n q tmp N ; 2 m; 3 whle do 4 n tmp/q ; 5 tmp tmp n q ; 6 ; Property II.2 ([, Proposton 2]). Gven (η ) N the sequence of the sgned partal remanders of any rratonal 0 <α<, every real β, wth 0 β<can be unquely wrtten as β = α + + b η where the followng Markovan condtons are verfed: { 0 b k, 0 b k, for 2, b =0f b + = k +. There also exsts two other number systems that are dual to these two. One decomposes ntegers n the bass (( ) q ) N and the other decomposes reals n the bass of the unsgned partal remanders (θ ) N []. The second Markovan condton then becomes b + =0f b = k. An algorthm to wrte real numbers n the (θ ) N number scale has been proposed by Ito [5]. It proceeds by teratng the mappng T :(α, β) (/α /α,β/α β/α ). C. Related number systems over ratonal numbers In ths subsecton, we consder α = p/q ratonal. We recall that the contnued fracton expanson of a ratonal s fnte. We denote p q =[0;k,k 2,...,k n ] the contnued fracton expanson of p/q, and recall p n = p and q n = q. We can stll wrte any nteger N usng the fnte sequence (q ) n and a greedy algorthm. However, the frst quotent N/q n wll not respect the Markovan condtons for N q n, as the condton s not defned for ths quotent (there s no k n+ ). Nevertheless, the Markovan condtons wll stll hold for ntegers N<q n, snce the keypont n the Ostrowsk number system s that there exsts q m such that q m >N [4]. The (η ) <n number system also stll holds under one supplemental condton: β must be ratonal wth precson at most q (.e. the denomnator of β must be less or equal than q). III. MODULAR ARITHMETIC AND CONTINUED FRACTION In ths secton, we consder α = a/d. We hghlght that the same decomposton (b,...,b n+ ) can be nterpreted n two ways dependng on the number system used. In the Ostrowsk number system, we obtan an nteger N whereas n the number scale (η ) N, we obtan the reduced value of Nα mod []. Hence, we wll use the fact that studyng an nteger a modulo d s smlar to consderng the ratonal a/d modulo. Ths enables us to use propertes II. and II.2 to compute modular multplcaton and dvson. A. Modular arthmetc and contnued fracton Frst, we brefly recall how contnued fracton expanson and the Eucldean algorthm are lnked. We wrte (θ ) N the nteger sequence of remanders when computng gcd(a, d). Ths sequence s composed of decreasng values less than d. We also wrte (η ) N 38
3 the sequence (( ) θ ) N. We obtan the followng recurrence relaton, and recall the recurrence relaton over the (θ ) N sequence of partal remanders of the contnued fracton expanson of a/d : θ = d θ 0 = a θ = θ 2 θ 2 /θ θ θ = θ 0 = a/d θ = θ 2 θ 2 /θ θ. It has to be notced that θ = dθ as the extended Eucldean algorthm compute the relatons θ = ( ) (q a p d) and θ =( ) a (q d p ). In partcular, ths mples that the same partal quotents, noted k, are obtaned when computng both sequences. Fnally, we notce that the extended Eucldean algorthm gves the Bezout s dentty wth θ n = ( ) n (q n a p n d) = gcd(a, d), and q n the nverse of a f a s nvertble modulo d (gcd(a, d) =). B. Modular multplcaton Now, gven a, b Z/dZ, we wrte c = a b mod d the nteger 0 c<dsuch that ab ab/d d = c. We can observe that the decompostons presented n propertes II. and II.2 are both unque and both need the same Markovan condton over ther coeffcents. Hence, we can nterpret the same decomposton n both bass. Theorem III.. Gven a, b Z/dZ, and (q ) n, (η ) n from Eucldean algorthm on a and d, f we wrte b n the (q ) n number scale as then n+ b =+ b q, n+ a b mod d = a + b η. Proof: Frst, we consder b<q n, t can be wrtten n the Ostrowsk number system as n b =+ b q, and the coeffcents b respect the Markovan condton of the Ostrowsk number system. Hence, n α b = α + b q α. By defnton, η = q α p, thus n α b = α + b η + n b p. θ k q b b rem Table I EXECUTION OF THE PROPOSED MODULAR MULTIPLICATION ALGORITHM WITH d =45, a =7AND b =30. As the coeffcents b s verfy the Markovan condton, the unqueness of the decomposton n property II.2 gves 0 α + n b η < and n b p N. Hence, n α b mod = α + b η. By multplyng ths nequalty by d, asα = a/d and η = η d, we obtan n a b mod d = a + b η. whch fnalzes the proof of the theorem for b<q n. Now f b q n and b = b n+ q n + b wth b <q n the remander of the dvson of b by q n, b can be unquely wrtten n the Ostrowsk number system. Furthermore, as η n =0, b n+ η n =0, whch fnshes the proof. Example III.. We gve n Table I the sequences nvolved n theorem III.2 wth d = 45, a = 7 and b =24. We denote (b rem ) N the sequence of remanders generated by the greedy decomposton of b n the (q ) N number scale. One can notce that b = , and that b a =24 7 = 3 mod d = C. Modular dvson Inversely, gven a, b Z/dZ, wth a nvertble modulo d (gcd(a, d) = ) we can effcently compute a b mod d. Theorem III.2. Gven a, b Z/dZ wth gcd(a, d) =, and (q ) n, (θ ) n from Eucldean algorthm on a and 39
4 d, f we wrte b n the (θ ) <n number scale as n+ b = b θ, n+ then f we denote c = b ( ) q, a b mod d {c, d + c}. Proof: The proof of correctness s smlar to the one of theorem III., usng the facts that θ = θ d and that θ =( ) (q α p ). Now, the greatest nteger c s clearly the one assocated to the decomposton (k, 0,k 3, 0,...,k n ) when n s odd. However, k q = q q 2 by defnton, whch mples (n )/2 =0 k 2+ q 2 = q n. The smallest nteger that can be returned s clearly the one assocated to the decomposton (0,k 2, 0,k 4,...,k n ) when n s even. Once agan, as k q = q q 2,we get n/2 k 2 q 2 = q n. Hence, d < n+ b ( ) q <d, that s to say, the result needs at most a correcton by an addton by d. Example III.2. We gve n Table II the sequences nvolved n theorem III.2 wth d =45, a =7and b =30. We here notce that b = , and that b a =30 8 = 5 mod d = We menton that we also tred to decompose b n the (η ) n sgned remanders number scale and evaluate ths same decomposton n the (q ) n number scale to compute modular dvson. We used Ito T 2 transform [5] T 2 : (α, β) (/α /α, β/α β/α). In practce, t returns the rght result wthout the need of any correcton. However, as the decomposton computed by Ito T 2 transform does not verfy the same Markovan condtons as n the Ostrowsk number system, we were not able to gve a theoretcal proof that t always returns the reduced result of the modular dvson. θ k q b b rem Table II EXECUTION OF THE PROPOSED MODULAR DIVISION ALGORITHM WITH d =45, a =7AND b =30. IV. ELEMENTS OF COMPLEXITY ANALYSIS In ths secton, we ntroduce elements of complexty analyss of the proposed modular multplcaton algorthm based on theorem III.. The same analyss holds for the dvson. Ths analyss s hghly eased by prevous works on the Eucldean algorthm complexty []. A. Worst-case complexty The ntroduced algorthms compute (q ) n and (η ) n. Ths can be computed usng the classcal extended Eucldean algorthm n O(log (d) 2 ) bnary operatons. Second, the bnary complexty of the decomposton n (q ) n as n algorthm s bounded by the complexty of computng the sequence (q ) n snce the same number of quotents are computed, wth values of smlar sze, and the quotents b are bounded by the quotents k (Markovan condton). Hence, the greedy decomposton has complexty n O(log (d) 2 ). To fnsh the worst-case complexty analyss, evaluatng the sum to return the fnal result can also be done n O(log (d) 2 ). B. Average number of quotents k The average number of quotents k computed by the Eucldean algorthm has been extensvely studed [6], [7], [8]. In partcular, Porter [9] showed that t s bounded by 2 ln(2) π 2 ln(d)+(4p +2, 5) + O(d /6+ɛ ) () for every ɛ>0 and P Porter s constant (P.47 and 2 ln(2)/π [0]). C. Average value of quotents k and b The average value of the quotents k s equal to Khnchn s constant (approxmately 2.69) [3, p. 93]. Furthermore, bg quotents are very unlkely to occur as 40
5 the quotents of any contnued fracton follow the Gauss- Kuzmn dstrbuton [3, p. 83] [7, p. 352], ) P(k = k) = log 2 ( (k +) 2. Ths typcally means that most of the dvsons computed n the Eucldean algorthm can be computed by subtracton effcently. By the same arguments, the coeffcents b of the decomposton n (q ) n can be computed by subtracton as they are also lkely small (as they are bounded by the k due to the Markovan condtons). In the modular multplcaton algorthm, the only quotent not followng the Gauss-Kuzmn dstrbuton s the coeffcent b n+ when gcd(a, d), as t corresponds to the quotent b/q n. Here, we prove the folowng theorem, showng that b n+ s stll lkely to be very small. Theorem IV.. Let a, d, b and N ntegers. If a and d are unformly chosen n [,N] and b s unformly chosen n [,d], then when N tends to nfnty, P(b n+ k) tends to [ k+ ζ(2) (k +) 3 ] +(k +)ζ(3). wth ζ(s) = + the Remann zeta functon. s Proof: Let U,U 2 and U 3 be three ndependent unform dstrbutons over [0, ]. We wrte a = U N, d = U 2 N and b = U 3 d. We denote A = {b <(k+)q n }, B = {gcd(a, d) k +}, B = {gcd(a, d) >k+} and B = {gcd(a, d) =}. Hence usng the law of total probablty we have A =(A B) (A B), = (A B ) ( ) (A B ), k+ >k+ = P(A B ) P(B ) ( ) P(A B ) P(B ). k+ >k+ As the B are dsjont events, we have P(A) = k+ P(A B ) P(B )+ + =k+2 P(A B ) P(B ). Frst, P(A B )=for k+ as b<d=gcd(a, d) q n (k +) q n. Hence, k+ + P(A) = P(B )+ P(A B ) P(B ). =k+2 Now we want to determne P(A B ) for k +2. Hereafter, to smplfy equatons, we wrte Q ( ) = P( B ) and C = {a = l} {d = m}. P(A B )=Q (A), N N = Q (C) Q (A C). l= m= However, Q (A C) = k + as b s unformly dstrbuted between and d = q n. If we consder the segment of length d and slce t n segments of length q n, t can be nterpreted as the probablty that b s n the frst k + slces. Hence P(A B )= N N l= m= = k + Q ({a = l} {d = m}) k +, N l= m= N Q ({a = l} {d = m}). As {a = l} and {d = m} are ndependent by hypothess (U and U 2 are ndependent), Q ({a = l} {d = m}) =Q ({a = l}) Q ({d = m}), and P(A B )= k + N N Q ({a = l}) Q ({d = m}). l= m= Now, we use the fact that the sum of the probabltes over the whole sample space always sum to to obtan P(A B )= k +. If we recaptulate, P(A) = k+ P(B )+ + =k+2 k + P(B ). Fnally, t s wdely known that P(B ) tends to ζ(2) 2 when N tends to nfnty [, p. 353]. Hence, we get lm P(A) = k+ N + ζ(2) 2 + [ k+ = ζ(2) =k+2 k (k +) ζ(2) 2, ] =k+2 3, 4
6 Probablty Fgure Max expected b n+ Cumulatve dstrbuton functon of the coeffcent b n+. whch equals to [ k+ ( ζ(2) + +(k +) 2 3 k+ [ k+ = ζ(2) (k +) 3 +(k +) ( + )], 3 3 )] Hence, usng Remann zeta functon defnton, we get the followng smplfcaton, whch s more convenent for computaton and has been used to generate Fg., lm N + P(A)=ζ(2) [ k+ (k +) 3 +(k+) ζ(3) Fgure shows the probablty dstrbuton of P(b n+ k). In partcular, we obtan P(b n+ 3) 92.5%. V. COMMENTS ON A PRACTICAL USE OF THESE ALGORITHMS Exstng algorthms for modular multplcaton are of two knds. They ether ntegrate the reducton, makng t possble to do all the computatons wth the nput precson (Blakley [2] and Takag [3]), or they rely on an effcent multplcaton of the arguments, and then effcently reduce ther product whch sze s the sum of the arguments sze (Barrett [4] and Montgomery [5]). All these algorthms are usually used n dfferent contexts, whether we compute many multplcatons by the same large values (Montgomery [5]) or small values (Takag[3]), or whether we compute few multplcatons. ]. by small values (Blakley [2]) or large values (Barrett [4]). The proposed algorthms are of the frst knd wth ntegrated reducton and do not need converson or pre-computaton. They clearly target contexts where few multplcatons of small values (because of the quadratc complexty) are computed. The proposed modular multplcaton seems to be of lttle nterest n practce n ts current form, as ts memory consumpton mght be hgh the sequences (θ ) N and (q ) N have to be stored entrely to decompose b and recompose the result even f t s of same complexty as competng methods (Blakley[2] and Takag[3]). Concernng the modular dvson, to our knowledge, all exstng algorthms requre to multply by an nverse whch need to be computed. In the proposed modular dvson, the modular multplcaton s ntegrated to the computaton of the nverse. Ths enables to partally cover the latency of the nverse computaton. Moreover, ts memory footprnt s low snce the computed sequences do not need to be stored. Frst experments wth a straghtforward 64-bt mplementaton show an encouragng speedup of 2.44x aganst GMP [6] low-level functons (mpn_gcd_ext, mpn_mul and mpn_tdv_qr). These arguments make t sutable n some context lke Gaussan elmnaton on a small dmenson matrx wth coeffcents n a fnte feld. For each row, several values are dvded by the same pvot. The proposed modular dvson helps coverng the latency of computng an nverse, seems adapted to decompose several nputs at the same tme (lke any greedy algorthm) and can be easly vectorzed (f a vectorzed nteger dvson nstructon s avalable). VI. PERSPECTIVES In ths paper, we presented an algorthm for modular multplcaton and an algorthm for modular dvson. Both are based on the extended Eucldean algorthm and are of quadratc complexty n the sze of the modulus,and do not requre pre-computaton or changng the nputs representaton. They present a theoretcal nterest snce t t the frst use of Ostrowsk number systems to ths purpose. Even though the proposed modular multplcaton algorthm n ts actual form s not relevant n practce, the modular dvson seems to be effcent as t ntegrate the multplcaton to the computaton of the nverse. Further nvestgatons have to be led to fnd optmal decomposton algorthms, that mnmze the number of coeffcents of the produced decomposton and ther 42
7 sze. Also, a supplemental effort s necessary to provde effcent software mplementaton of the modular dvson algorthm. VII. AKNOWLEDGEMENT Ths work was supported by the TaMaD project of the french ANR (grant ANR 200 BLAN ). Ths work has also been greatly supported and mproved by many helpful proof readngs and dscussons wth Jean- Claude Bajard, Valére Berthé, Perre Fortn, Stef Grallat and Emmanuel Prouff. REFERENCES [] V. Berthé and L. Imbert, Dophantne approxmaton, Ostrowsk numeraton and the double-base number system, Dscrete Mathematcs & Theoretcal Computer Scence, vol., no., pp , [2] R. Brent and P. Zmmermann, Modern computer arthmetc, vol. 8. Cambrdge Unversty Press, 200. [3] A. Y. Khnchn, Contnued fractons. Dover, 997. [4] A. Vershk and N. Sdorov, Arthmetc expansons assocated wth a rotaton of the crcle and wth contnued fractons, Sant Petersburg Mathematcal Journal, vol. 5, no. 6, pp. 2-36, 994. [5] S. Ito, Some skew product transformatons assocated wth contnued fractons and ther nvarant measures, Tokyo Journal of Mathematcs, vol. 9, no., pp. 5 33, 986. [6] B. Vallée, Eucldeans dynamcs, Dscrete and Contnuous Dynamcal Systems seres S, pp , [7] D. E. Knuth, The Art of Computer Programmng, vol. 2 (Semnumercal Algorthms). Addson-Wesley, second ed., 98. [8] L. Lhote and B. Vallée, Gaussan laws for the man parameters of the Eucld algorthms, Algorthmca, vol. 50, no. 4, pp , [9] J. W. Porter, On a theorem of Helbronn, Mathematka, vol. 22, no. 0, pp , 975. [0] D. E. Knuth, Evaluaton of Porter s constant, Computers & Mathematcs wth Applcatons, vol. 2, no. 2, pp , 976. [] G. H. Hardy and E. M. Wrght, An Introducton to the Theory of Numbers. Oxford Unversty Press, 6 th ed., [2] G. Blakley, A computer algorthm for calculatng the product ab modulo m, IEEE Transactons on Computers, vol. 32, no. 5, pp , 983. [3] N. Takag, A radx-4 modular multplcaton hardware algorthm for modular exponentaton, Computers, IEEE Transactons on, vol. 4, no. 8, pp , 992. [4] P. Barrett, Implementng the Rvest Shamr and Adleman publc key encrypton algorthm on a standard dgtal sgnal processor, n Advances n cryptology CRYPTO 86, pp , Sprnger, 987. [5] P. L. Montgomery, Modular multplcaton wthout tral dvson, Mathematcs of computaton, vol. 44, no. 70, pp , 985. [6] T. Granlund and the GMP development team, GNU MP, ed., January
New modular multiplication and division algorithms based on continued fraction expansion
New modular multplcaton and dvson algorthms based on contnued fracton expanson Mourad Goucem a a UPMC Unv Pars 06 and CNRS UMR 7606, LIP6 4 place Jusseu, F-75252, Pars cedex 05, France Abstract In ths
More informationFoundations of Arithmetic
Foundatons of Arthmetc Notaton We shall denote the sum and product of numbers n the usual notaton as a 2 + a 2 + a 3 + + a = a, a 1 a 2 a 3 a = a The notaton a b means a dvdes b,.e. ac = b where c s an
More informationLectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix
Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could
More informationInner Product. Euclidean Space. Orthonormal Basis. Orthogonal
Inner Product Defnton 1 () A Eucldean space s a fnte-dmensonal vector space over the reals R, wth an nner product,. Defnton 2 (Inner Product) An nner product, on a real vector space X s a symmetrc, blnear,
More informationThe Order Relation and Trace Inequalities for. Hermitian Operators
Internatonal Mathematcal Forum, Vol 3, 08, no, 507-57 HIKARI Ltd, wwwm-hkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence
More informationErrors for Linear Systems
Errors for Lnear Systems When we solve a lnear system Ax b we often do not know A and b exactly, but have only approxmatons  and ˆb avalable. Then the best thng we can do s to solve ˆx ˆb exactly whch
More informationExample: (13320, 22140) =? Solution #1: The divisors of are 1, 2, 3, 4, 5, 6, 9, 10, 12, 15, 18, 20, 27, 30, 36, 41,
The greatest common dvsor of two ntegers a and b (not both zero) s the largest nteger whch s a common factor of both a and b. We denote ths number by gcd(a, b), or smply (a, b) when there s no confuson
More informationSpeeding up Computation of Scalar Multiplication in Elliptic Curve Cryptosystem
H.K. Pathak et. al. / (IJCSE) Internatonal Journal on Computer Scence and Engneerng Speedng up Computaton of Scalar Multplcaton n Ellptc Curve Cryptosystem H. K. Pathak Manju Sangh S.o.S n Computer scence
More informationNUMERICAL DIFFERENTIATION
NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the
More informationFinding Primitive Roots Pseudo-Deterministically
Electronc Colloquum on Computatonal Complexty, Report No 207 (205) Fndng Prmtve Roots Pseudo-Determnstcally Ofer Grossman December 22, 205 Abstract Pseudo-determnstc algorthms are randomzed search algorthms
More information2.3 Nilpotent endomorphisms
s a block dagonal matrx, wth A Mat dm U (C) In fact, we can assume that B = B 1 B k, wth B an ordered bass of U, and that A = [f U ] B, where f U : U U s the restrcton of f to U 40 23 Nlpotent endomorphsms
More information2 More examples with details
Physcs 129b Lecture 3 Caltech, 01/15/19 2 More examples wth detals 2.3 The permutaton group n = 4 S 4 contans 4! = 24 elements. One s the dentty e. Sx of them are exchange of two objects (, j) ( to j and
More informationLecture 3. Ax x i a i. i i
18.409 The Behavor of Algorthms n Practce 2/14/2 Lecturer: Dan Spelman Lecture 3 Scrbe: Arvnd Sankar 1 Largest sngular value In order to bound the condton number, we need an upper bound on the largest
More informationLecture 12: Discrete Laplacian
Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly
More informationSection 8.3 Polar Form of Complex Numbers
80 Chapter 8 Secton 8 Polar Form of Complex Numbers From prevous classes, you may have encountered magnary numbers the square roots of negatve numbers and, more generally, complex numbers whch are the
More informationDirichlet s Theorem In Arithmetic Progressions
Drchlet s Theorem In Arthmetc Progressons Parsa Kavkan Hang Wang The Unversty of Adelade February 26, 205 Abstract The am of ths paper s to ntroduce and prove Drchlet s theorem n arthmetc progressons,
More informationLecture 4: Universal Hash Functions/Streaming Cont d
CSE 5: Desgn and Analyss of Algorthms I Sprng 06 Lecture 4: Unversal Hash Functons/Streamng Cont d Lecturer: Shayan Oves Gharan Aprl 6th Scrbe: Jacob Schreber Dsclamer: These notes have not been subjected
More informationAPPENDIX A Some Linear Algebra
APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,
More informationU.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016
U.C. Berkeley CS94: Spectral Methods and Expanders Handout 8 Luca Trevsan February 7, 06 Lecture 8: Spectral Algorthms Wrap-up In whch we talk about even more generalzatons of Cheeger s nequaltes, and
More informationSL n (F ) Equals its Own Derived Group
Internatonal Journal of Algebra, Vol. 2, 2008, no. 12, 585-594 SL n (F ) Equals ts Own Derved Group Jorge Macel BMCC-The Cty Unversty of New York, CUNY 199 Chambers street, New York, NY 10007, USA macel@cms.nyu.edu
More informationn α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0
MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector
More informationAn efficient algorithm for multivariate Maclaurin Newton transformation
Annales UMCS Informatca AI VIII, 2 2008) 5 14 DOI: 10.2478/v10065-008-0020-6 An effcent algorthm for multvarate Maclaurn Newton transformaton Joanna Kapusta Insttute of Mathematcs and Computer Scence,
More informationThe internal structure of natural numbers and one method for the definition of large prime numbers
The nternal structure of natural numbers and one method for the defnton of large prme numbers Emmanul Manousos APM Insttute for the Advancement of Physcs and Mathematcs 3 Poulou str. 53 Athens Greece Abstract
More informationStanford University CS359G: Graph Partitioning and Expanders Handout 4 Luca Trevisan January 13, 2011
Stanford Unversty CS359G: Graph Parttonng and Expanders Handout 4 Luca Trevsan January 3, 0 Lecture 4 In whch we prove the dffcult drecton of Cheeger s nequalty. As n the past lectures, consder an undrected
More informationNumerical Heat and Mass Transfer
Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and
More informationSalmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2
Salmon: Lectures on partal dfferental equatons 5. Classfcaton of second-order equatons There are general methods for classfyng hgher-order partal dfferental equatons. One s very general (applyng even to
More informationMore metrics on cartesian products
More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of
More informationComplex Numbers. x = B B 2 4AC 2A. or x = x = 2 ± 4 4 (1) (5) 2 (1)
Complex Numbers If you have not yet encountered complex numbers, you wll soon do so n the process of solvng quadratc equatons. The general quadratc equaton Ax + Bx + C 0 has solutons x B + B 4AC A For
More informationLecture 2: Gram-Schmidt Vectors and the LLL Algorithm
NYU, Fall 2016 Lattces Mn Course Lecture 2: Gram-Schmdt Vectors and the LLL Algorthm Lecturer: Noah Stephens-Davdowtz 2.1 The Shortest Vector Problem In our last lecture, we consdered short solutons to
More informationarxiv: v1 [math.ho] 18 May 2008
Recurrence Formulas for Fbonacc Sums Adlson J. V. Brandão, João L. Martns 2 arxv:0805.2707v [math.ho] 8 May 2008 Abstract. In ths artcle we present a new recurrence formula for a fnte sum nvolvng the Fbonacc
More informationFINITELY-GENERATED MODULES OVER A PRINCIPAL IDEAL DOMAIN
FINITELY-GENERTED MODULES OVER PRINCIPL IDEL DOMIN EMMNUEL KOWLSKI Throughout ths note, s a prncpal deal doman. We recall the classfcaton theorem: Theorem 1. Let M be a fntely-generated -module. (1) There
More informationGrover s Algorithm + Quantum Zeno Effect + Vaidman
Grover s Algorthm + Quantum Zeno Effect + Vadman CS 294-2 Bomb 10/12/04 Fall 2004 Lecture 11 Grover s algorthm Recall that Grover s algorthm for searchng over a space of sze wors as follows: consder the
More informationa b a In case b 0, a being divisible by b is the same as to say that
Secton 6.2 Dvsblty among the ntegers An nteger a ε s dvsble by b ε f there s an nteger c ε such that a = bc. Note that s dvsble by any nteger b, snce = b. On the other hand, a s dvsble by only f a = :
More informationChapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems
Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons
More informationNotes on Frequency Estimation in Data Streams
Notes on Frequency Estmaton n Data Streams In (one of) the data streamng model(s), the data s a sequence of arrvals a 1, a 2,..., a m of the form a j = (, v) where s the dentty of the tem and belongs to
More informationCOMPLEX NUMBERS AND QUADRATIC EQUATIONS
COMPLEX NUMBERS AND QUADRATIC EQUATIONS INTRODUCTION We know that x 0 for all x R e the square of a real number (whether postve, negatve or ero) s non-negatve Hence the equatons x, x, x + 7 0 etc are not
More informationStanford University CS254: Computational Complexity Notes 7 Luca Trevisan January 29, Notes for Lecture 7
Stanford Unversty CS54: Computatonal Complexty Notes 7 Luca Trevsan January 9, 014 Notes for Lecture 7 1 Approxmate Countng wt an N oracle We complete te proof of te followng result: Teorem 1 For every
More informationFormulas for the Determinant
page 224 224 CHAPTER 3 Determnants e t te t e 2t 38 A = e t 2te t e 2t e t te t 2e 2t 39 If 123 A = 345, 456 compute the matrx product A adj(a) What can you conclude about det(a)? For Problems 40 43, use
More informationModule 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:
More informationLOW BIAS INTEGRATED PATH ESTIMATORS. James M. Calvin
Proceedngs of the 007 Wnter Smulaton Conference S G Henderson, B Bller, M-H Hseh, J Shortle, J D Tew, and R R Barton, eds LOW BIAS INTEGRATED PATH ESTIMATORS James M Calvn Department of Computer Scence
More information8.6 The Complex Number System
8.6 The Complex Number System Earler n the chapter, we mentoned that we cannot have a negatve under a square root, snce the square of any postve or negatve number s always postve. In ths secton we want
More information3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X
Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number
More informationBernoulli Numbers and Polynomials
Bernoull Numbers and Polynomals T. Muthukumar tmk@tk.ac.n 17 Jun 2014 The sum of frst n natural numbers 1, 2, 3,..., n s n n(n + 1 S 1 (n := m = = n2 2 2 + n 2. Ths formula can be derved by notng that
More informationTransfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system
Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng
More informationLecture 10 Support Vector Machines II
Lecture 10 Support Vector Machnes II 22 February 2016 Taylor B. Arnold Yale Statstcs STAT 365/665 1/28 Notes: Problem 3 s posted and due ths upcomng Frday There was an early bug n the fake-test data; fxed
More informationAttacks on RSA The Rabin Cryptosystem Semantic Security of RSA Cryptology, Tuesday, February 27th, 2007 Nils Andersen. Complexity Theoretic Reduction
Attacks on RSA The Rabn Cryptosystem Semantc Securty of RSA Cryptology, Tuesday, February 27th, 2007 Nls Andersen Square Roots modulo n Complexty Theoretc Reducton Factorng Algorthms Pollard s p 1 Pollard
More informationEEE 241: Linear Systems
EEE : Lnear Systems Summary #: Backpropagaton BACKPROPAGATION The perceptron rule as well as the Wdrow Hoff learnng were desgned to tran sngle layer networks. They suffer from the same dsadvantage: they
More informationProblem Set 9 Solutions
Desgn and Analyss of Algorthms May 4, 2015 Massachusetts Insttute of Technology 6.046J/18.410J Profs. Erk Demane, Srn Devadas, and Nancy Lynch Problem Set 9 Solutons Problem Set 9 Solutons Ths problem
More informationGeneralized Linear Methods
Generalzed Lnear Methods 1 Introducton In the Ensemble Methods the general dea s that usng a combnaton of several weak learner one could make a better learner. More formally, assume that we have a set
More informationAn (almost) unbiased estimator for the S-Gini index
An (almost unbased estmator for the S-Gn ndex Thomas Demuynck February 25, 2009 Abstract Ths note provdes an unbased estmator for the absolute S-Gn and an almost unbased estmator for the relatve S-Gn for
More informationContinuous Time Markov Chains
Contnuous Tme Markov Chans Brth and Death Processes,Transton Probablty Functon, Kolmogorov Equatons, Lmtng Probabltes, Unformzaton Chapter 6 1 Markovan Processes State Space Parameter Space (Tme) Dscrete
More informationA new Approach for Solving Linear Ordinary Differential Equations
, ISSN 974-57X (Onlne), ISSN 974-5718 (Prnt), Vol. ; Issue No. 1; Year 14, Copyrght 13-14 by CESER PUBLICATIONS A new Approach for Solvng Lnear Ordnary Dfferental Equatons Fawz Abdelwahd Department of
More information5 The Rational Canonical Form
5 The Ratonal Canoncal Form Here p s a monc rreducble factor of the mnmum polynomal m T and s not necessarly of degree one Let F p denote the feld constructed earler n the course, consstng of all matrces
More informationREGULAR POSITIVE TERNARY QUADRATIC FORMS. 1. Introduction
REGULAR POSITIVE TERNARY QUADRATIC FORMS BYEONG-KWEON OH Abstract. A postve defnte quadratc form f s sad to be regular f t globally represents all ntegers that are represented by the genus of f. In 997
More informationIntroduction to Information Theory, Data Compression,
Introducton to Informaton Theory, Data Compresson, Codng Mehd Ibm Brahm, Laura Mnkova Aprl 5, 208 Ths s the augmented transcrpt of a lecture gven by Luc Devroye on the 3th of March 208 for a Data Structures
More information18.1 Introduction and Recap
CS787: Advanced Algorthms Scrbe: Pryananda Shenoy and Shjn Kong Lecturer: Shuch Chawla Topc: Streamng Algorthmscontnued) Date: 0/26/2007 We contnue talng about streamng algorthms n ths lecture, ncludng
More informationInexact Newton Methods for Inverse Eigenvalue Problems
Inexact Newton Methods for Inverse Egenvalue Problems Zheng-jan Ba Abstract In ths paper, we survey some of the latest development n usng nexact Newton-lke methods for solvng nverse egenvalue problems.
More informationTHE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens
THE CHINESE REMAINDER THEOREM KEITH CONRAD We should thank the Chnese for ther wonderful remander theorem. Glenn Stevens 1. Introducton The Chnese remander theorem says we can unquely solve any par of
More informationA Hybrid Variational Iteration Method for Blasius Equation
Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 1 (June 2015), pp. 223-229 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) A Hybrd Varatonal Iteraton Method
More information18.781: Solution to Practice Questions for Final Exam
18.781: Soluton to Practce Questons for Fnal Exam 1. Fnd three solutons n postve ntegers of x 6y = 1 by frst calculatng the contnued fracton expanson of 6. Soluton: We have 1 6=[, ] 6 6+ =[, ] 1 =[,, ]=[,,
More informationGlobal Sensitivity. Tuesday 20 th February, 2018
Global Senstvty Tuesday 2 th February, 28 ) Local Senstvty Most senstvty analyses [] are based on local estmates of senstvty, typcally by expandng the response n a Taylor seres about some specfc values
More informationFirst day August 1, Problems and Solutions
FOURTH INTERNATIONAL COMPETITION FOR UNIVERSITY STUDENTS IN MATHEMATICS July 30 August 4, 997, Plovdv, BULGARIA Frst day August, 997 Problems and Solutons Problem. Let {ε n } n= be a sequence of postve
More informationMATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS
MATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS These are nformal notes whch cover some of the materal whch s not n the course book. The man purpose s to gve a number of nontrval examples
More informationDigital Signal Processing
Dgtal Sgnal Processng Dscrete-tme System Analyss Manar Mohasen Offce: F8 Emal: manar.subh@ut.ac.r School of IT Engneerng Revew of Precedent Class Contnuous Sgnal The value of the sgnal s avalable over
More informationVector Norms. Chapter 7 Iterative Techniques in Matrix Algebra. Cauchy-Bunyakovsky-Schwarz Inequality for Sums. Distances. Convergence.
Vector Norms Chapter 7 Iteratve Technques n Matrx Algebra Per-Olof Persson persson@berkeley.edu Department of Mathematcs Unversty of Calforna, Berkeley Math 128B Numercal Analyss Defnton A vector norm
More informationTAIL BOUNDS FOR SUMS OF GEOMETRIC AND EXPONENTIAL VARIABLES
TAIL BOUNDS FOR SUMS OF GEOMETRIC AND EXPONENTIAL VARIABLES SVANTE JANSON Abstract. We gve explct bounds for the tal probabltes for sums of ndependent geometrc or exponental varables, possbly wth dfferent
More informationPolynomials. 1 What is a polynomial? John Stalker
Polynomals John Stalker What s a polynomal? If you thnk you already know what a polynomal s then skp ths secton. Just be aware that I consstently wrte thngs lke p = c z j =0 nstead of p(z) = c z. =0 You
More informationDISCRIMINANTS AND RAMIFIED PRIMES. 1. Introduction A prime number p is said to be ramified in a number field K if the prime ideal factorization
DISCRIMINANTS AND RAMIFIED PRIMES KEITH CONRAD 1. Introducton A prme number p s sad to be ramfed n a number feld K f the prme deal factorzaton (1.1) (p) = po K = p e 1 1 peg g has some e greater than 1.
More informationAPPROXIMATE PRICES OF BASKET AND ASIAN OPTIONS DUPONT OLIVIER. Premia 14
APPROXIMAE PRICES OF BASKE AND ASIAN OPIONS DUPON OLIVIER Prema 14 Contents Introducton 1 1. Framewor 1 1.1. Baset optons 1.. Asan optons. Computng the prce 3. Lower bound 3.1. Closed formula for the prce
More informationU.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017
U.C. Berkeley CS94: Beyond Worst-Case Analyss Handout 4s Luca Trevsan September 5, 07 Summary of Lecture 4 In whch we ntroduce semdefnte programmng and apply t to Max Cut. Semdefnte Programmng Recall that
More informationOn a direct solver for linear least squares problems
ISSN 2066-6594 Ann. Acad. Rom. Sc. Ser. Math. Appl. Vol. 8, No. 2/2016 On a drect solver for lnear least squares problems Constantn Popa Abstract The Null Space (NS) algorthm s a drect solver for lnear
More informationCurvature and isoperimetric inequality
urvature and sopermetrc nequalty Julà ufí, Agustí Reventós, arlos J Rodríguez Abstract We prove an nequalty nvolvng the length of a plane curve and the ntegral of ts radus of curvature, that has as a consequence
More informationReport on Image warping
Report on Image warpng Xuan Ne, Dec. 20, 2004 Ths document summarzed the algorthms of our mage warpng soluton for further study, and there s a detaled descrpton about the mplementaton of these algorthms.
More informationIntroduction to Algorithms
Introducton to Algorthms 6.046J/8.40J Lecture 7 Prof. Potr Indyk Data Structures Role of data structures: Encapsulate data Support certan operatons (e.g., INSERT, DELETE, SEARCH) Our focus: effcency of
More informationP A = (P P + P )A = P (I P T (P P ))A = P (A P T (P P )A) Hence if we let E = P T (P P A), We have that
Backward Error Analyss for House holder Reectors We want to show that multplcaton by householder reectors s backward stable. In partcular we wsh to show fl(p A) = P (A) = P (A + E where P = I 2vv T s the
More informationJournal of Universal Computer Science, vol. 1, no. 7 (1995), submitted: 15/12/94, accepted: 26/6/95, appeared: 28/7/95 Springer Pub. Co.
Journal of Unversal Computer Scence, vol. 1, no. 7 (1995), 469-483 submtted: 15/12/94, accepted: 26/6/95, appeared: 28/7/95 Sprnger Pub. Co. Round-o error propagaton n the soluton of the heat equaton by
More informationLinear Approximation with Regularization and Moving Least Squares
Lnear Approxmaton wth Regularzaton and Movng Least Squares Igor Grešovn May 007 Revson 4.6 (Revson : March 004). 5 4 3 0.5 3 3.5 4 Contents: Lnear Fttng...4. Weghted Least Squares n Functon Approxmaton...
More informationExercises. 18 Algorithms
18 Algorthms Exercses 0.1. In each of the followng stuatons, ndcate whether f = O(g), or f = Ω(g), or both (n whch case f = Θ(g)). f(n) g(n) (a) n 100 n 200 (b) n 1/2 n 2/3 (c) 100n + log n n + (log n)
More informationA summation on Bernoulli numbers
Journal of Number Theory 111 (005 37 391 www.elsever.com/locate/jnt A summaton on Bernoull numbers Kwang-Wu Chen Department of Mathematcs and Computer Scence Educaton, Tape Muncpal Teachers College, No.
More informationAlgorithms for factoring
CSA E0 235: Crytograhy Arl 9,2015 Instructor: Arta Patra Algorthms for factorng Submtted by: Jay Oza, Nranjan Sngh Introducton Factorsaton of large ntegers has been a wdely studed toc manly because of
More informationProblem Solving in Math (Math 43900) Fall 2013
Problem Solvng n Math (Math 43900) Fall 2013 Week four (September 17) solutons Instructor: Davd Galvn 1. Let a and b be two nteger for whch a b s dvsble by 3. Prove that a 3 b 3 s dvsble by 9. Soluton:
More informationAn Introduction to Morita Theory
An Introducton to Morta Theory Matt Booth October 2015 Nov. 2017: made a few revsons. Thanks to Nng Shan for catchng a typo. My man reference for these notes was Chapter II of Bass s book Algebrac K-Theory
More informationTOPICS MULTIPLIERLESS FILTER DESIGN ELEMENTARY SCHOOL ALGORITHM MULTIPLICATION
1 2 MULTIPLIERLESS FILTER DESIGN Realzaton of flters wthout full-fledged multplers Some sldes based on support materal by W. Wolf for hs book Modern VLSI Desgn, 3 rd edton. Partly based on followng papers:
More informationThe Geometry of Logit and Probit
The Geometry of Logt and Probt Ths short note s meant as a supplement to Chapters and 3 of Spatal Models of Parlamentary Votng and the notaton and reference to fgures n the text below s to those two chapters.
More informationOn the size of quotient of two subsets of positive integers.
arxv:1706.04101v1 [math.nt] 13 Jun 2017 On the sze of quotent of two subsets of postve ntegers. Yur Shtenkov Abstract We obtan non-trval lower bound for the set A/A, where A s a subset of the nterval [1,
More informationarxiv: v1 [quant-ph] 6 Sep 2007
An Explct Constructon of Quantum Expanders Avraham Ben-Aroya Oded Schwartz Amnon Ta-Shma arxv:0709.0911v1 [quant-ph] 6 Sep 2007 Abstract Quantum expanders are a natural generalzaton of classcal expanders.
More informationMMA and GCMMA two methods for nonlinear optimization
MMA and GCMMA two methods for nonlnear optmzaton Krster Svanberg Optmzaton and Systems Theory, KTH, Stockholm, Sweden. krlle@math.kth.se Ths note descrbes the algorthms used n the author s 2007 mplementatons
More informationThe Jacobsthal and Jacobsthal-Lucas Numbers via Square Roots of Matrices
Internatonal Mathematcal Forum, Vol 11, 2016, no 11, 513-520 HIKARI Ltd, wwwm-hkarcom http://dxdoorg/1012988/mf20166442 The Jacobsthal and Jacobsthal-Lucas Numbers va Square Roots of Matrces Saadet Arslan
More informationStructure and Drive Paul A. Jensen Copyright July 20, 2003
Structure and Drve Paul A. Jensen Copyrght July 20, 2003 A system s made up of several operatons wth flow passng between them. The structure of the system descrbes the flow paths from nputs to outputs.
More informationRestricted divisor sums
ACTA ARITHMETICA 02 2002) Restrcted dvsor sums by Kevn A Broughan Hamlton) Introducton There s a body of work n the lterature on varous restrcted sums of the number of dvsors of an nteger functon ncludng
More informationLecture 4: Constant Time SVD Approximation
Spectral Algorthms and Representatons eb. 17, Mar. 3 and 8, 005 Lecture 4: Constant Tme SVD Approxmaton Lecturer: Santosh Vempala Scrbe: Jangzhuo Chen Ths topc conssts of three lectures 0/17, 03/03, 03/08),
More informationVARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES
VARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES BÂRZĂ, Slvu Faculty of Mathematcs-Informatcs Spru Haret Unversty barza_slvu@yahoo.com Abstract Ths paper wants to contnue
More informationNotes prepared by Prof Mrs) M.J. Gholba Class M.Sc Part(I) Information Technology
Inverse transformatons Generaton of random observatons from gven dstrbutons Assume that random numbers,,, are readly avalable, where each tself s a random varable whch s unformly dstrbuted over the range(,).
More informationP R. Lecture 4. Theory and Applications of Pattern Recognition. Dept. of Electrical and Computer Engineering /
Theory and Applcatons of Pattern Recognton 003, Rob Polkar, Rowan Unversty, Glassboro, NJ Lecture 4 Bayes Classfcaton Rule Dept. of Electrcal and Computer Engneerng 0909.40.0 / 0909.504.04 Theory & Applcatons
More informationThe Exact Formulation of the Inverse of the Tridiagonal Matrix for Solving the 1D Poisson Equation with the Finite Difference Method
Journal of Electromagnetc Analyss and Applcatons, 04, 6, 0-08 Publshed Onlne September 04 n ScRes. http://www.scrp.org/journal/jemaa http://dx.do.org/0.46/jemaa.04.6000 The Exact Formulaton of the Inverse
More informationC/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1
C/CS/Phy9 Problem Set 3 Solutons Out: Oct, 8 Suppose you have two qubts n some arbtrary entangled state ψ You apply the teleportaton protocol to each of the qubts separately What s the resultng state obtaned
More informationEcon107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)
I. Classcal Assumptons Econ7 Appled Econometrcs Topc 3: Classcal Model (Studenmund, Chapter 4) We have defned OLS and studed some algebrac propertes of OLS. In ths topc we wll study statstcal propertes
More informationCHAPTER-5 INFORMATION MEASURE OF FUZZY MATRIX AND FUZZY BINARY RELATION
CAPTER- INFORMATION MEASURE OF FUZZY MATRI AN FUZZY BINARY RELATION Introducton The basc concept of the fuzz matr theor s ver smple and can be appled to socal and natural stuatons A branch of fuzz matr
More information8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS
SECTION 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS 493 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS All the vector spaces you have studed thus far n the text are real vector spaces because the scalars
More informationNumerical Properties of the LLL Algorithm
Numercal Propertes of the LLL Algorthm Frankln T. Luk a and Sanzheng Qao b a Department of Mathematcs, Hong Kong Baptst Unversty, Kowloon Tong, Hong Kong b Dept. of Computng and Software, McMaster Unv.,
More information